An image processing device that processes a plurality of non-perspective images captured at a plurality of different time points is known (for example, see Non-Patent Documents 1 and 2). Pixels included in a non-perspective image indicate a foreground or a background. For example, the foreground is a moving object such as a vehicle and the background is a static object such as a building and a road.
This image processing device determines whether a pixel indicates a foreground or a background based on a mixture normal distribution.
Specifically, the image processing device acquires a probability distribution of luminance of a pixel in a plurality of non-perspective images based on an occurrence frequency of a non-perspective image in which the luminance of the pixel has respective values of a plurality of values. In other words, the probability distribution of the luminance of the pixel indicates the percentage of the number of non-perspective images in which the luminance of the pixel has respective values of a plurality of values among the plurality of non-perspective images to the total number of non-perspective images, and the luminance of the pixel is used as a random variable.
Furthermore, the image processing device estimates a mixture normal distribution indicating the acquired probability distribution and determines whether the pixel indicates a foreground or a background based on the estimated mixture normal distribution.
For example, as illustrated in FIG. 1(A), the luminance of a pixel included in an image changes with a change in the time point at which the image was captured. In this case, the probability distribution of the luminance of the pixel is represented as in FIG. 1(B).
However, when a plurality of objects are present on a straight line extending along the direction in which a non-perspective image is captured, a pixel included in the non-perspective image indicates an object positioned on the foremost side. Therefore, when a foreground is a moving object, a period in which the pixel indicates a background may be longer than a period in which the pixel indicates a foreground.
Therefore, when the luminance of the pixel corresponds to a normal distribution G1 having the largest probability among a plurality of normal distributions G1 and G2 that form the estimated mixture normal distribution, the image processing device determines that the pixel indicates a background.
Non-Patent Documents 1: J. Choi, and two others, “Adaptive Shadow Estimator for Removing Shadow of Moving Object,” Computer Vision and Image Understanding, Elsevier Inc., 2010, Vol. 114, p. 1017-1029
Non-Patent Documents 2: S. Calderara, and two others, “Vision Based Smoke Detection System Using Image Energy and Color Information,” Machine Vision and Applications, Springer, 2010, Vol. 22, p. 705-719